AWS Data Exchange vs Denodo

• Simplified data delivery
• Ability to create any amount of data products
• Ability to integrate payment plans with data products
• Tracking data downloads and users
• Integration with other AWS data services

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• Flat learning curve.
• Does not need brilliant developers.
• Less need for custom denodo wrappers, even if needed is not very complex.
• Denodo stored procedures and functions helped address complex, not straightforward requirements.
• Export/import deployment between environments was very helpful.

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• Integration with more data sources
• Ability to deliver data to clients without AWS accounts
• Inclusion of direct data downloads in addition to asynchronous methods

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• Lack of Documentation and user community: Denodo continues to have a small community of super users, therefore there is not a lot of documentation out there in the event you get stuck.
• Cost: Data virtualization isn't cheap, so smaller organizations might shy away from this technology due to the high licensing costs.
• Caching strategy: Some slower datasets will require caching... which argues, why not just do traditional ETL if you need to do this?

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• Reduced time to publish datasets for sale by more than 80%
• Increased net profit from dataset sales by ~10%
• Reduced data delivery time to clients by 15%

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• Improved time-to-market. We addressed new requirements in less than 2 person days.
• Very agile. Easy to handle changing requirements. Like a new requirement, a change in requirement was not expensive either.
• Platform issues were difficult to diagnose and debug.

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